Wyniki wyszukiwania - BazTech

Ograniczanie wyników

1 Archives of Electrical Engineering

1 2025

Znaleziono wyników: 1

Liczba wyników na stronie

Wyniki wyszukiwania

Wyszukiwano:
w słowach kluczowych: multi-population genetic algorithm

Sortuj według:

Ogranicz wyniki do:

Cooperative optimization of temperature and thrust ripple in permanent magnet synchronous linear motors

Yan Jianglong, Li Yanzhe, Yang Yimeng, Liu Guoqing, Liu Yuantao

Archives of Electrical Engineering

2025

Vol. 74, nr 2

503--519

Temperature rise and thrust ripple in Permanent Magnet Synchronous Linear Motors are critical factors that impact their operational performance and stability. This study addresses the coupled effects of temperature variation and thrust ripple in Permanent Magnet Synchronous Linear Motors by proposing a cooperative optimization method aimed at enhancing stability and efficiency. A trapezoidal Halbach alternating electrode structure based Permanent Magnet Synchronous Linear Motors analytical model was developed. Combining the Multi-Population Genetic Algorithm with the Kriging surrogate model, a cooperative optimization framework was established to improve the precision and efficiency of temperature and thrust ripple optimization through iterative sample point addition and multi-objective strategies. Experimental results demonstrate that the proposed method reduces thrust fluctuation to 8.3%, which is lower than traditional methods. The utilization rate of the permanent magnet is higher than other methods, reaching 5.8 N/cm 3. The temperature rise is significantly reduced, achieving a maximum energy-saving rate of 25%, and the optimization efficiency improves by 43.5%. In addition, the reliability of the method is verified by COMSOL Multiphysics 6.0 finite element simulation combined with ANSYS Maxwell electromagnetic simulation. This research offers a novel approach to Permanent Magnet Synchronous Linear Motors optimization, providing technical insights for designing high-performance, energy-efficient motors.